scholarly journals Investigating higher order interactions in single cell data with scHOT

2019 ◽  
Author(s):  
Shila Ghazanfar ◽  
Yingxin Lin ◽  
Xianbin Su ◽  
David M. Lin ◽  
Ellis Patrick ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Expression Profiles ◽  
Order Effect ◽  
Higher Order ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Novel Approach ◽  
Fate Decision ◽  
Cell Data

ABSTRACTSingle-cell RNA-sequencing has transformed our ability to examine cell fate choice. For example, in the context of development and differentiation, computational ordering of cells along ‘pseudotime’ enables the expression profiles of individual genes, including key transcription factors, to be examined at fine scale temporal resolution. However, while cell fate decisions are typically marked by profound changes in expression, many such changes are observed in genes downstream of the initial cell fate decision. By contrast, the genes directly involved in the cell fate decision process are likely to interact in subtle ways, potentially resulting in observed changes in patterns of correlation and variation rather than mean expression prior to cell fate commitment. Herein, we describe a novel approach, scHOT – single cell Higher Order Testing - which provides a flexible and statistically robust framework for identifying changes in higher order interactions among genes. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. We demonstrate the utility of scHOT by studying embryonic development of the liver, where we find coordinated changes in higher order interactions of programs related to differentiation and liver function. We also demonstrate its ability to find subtle changes in gene-gene correlation patterns across space using spatially-resolved expression data from the mouse olfactory bulb. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.

scholarly journals Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tim Liebisch ◽  
Armin Drusko ◽  
Biena Mathew ◽  
Ernst H. K. Stelzer ◽  
Sabine C. Fischer ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Cell Division ◽  
Cell Fate ◽  
Inner Cell Mass ◽  
Cell Mass ◽  
Cell Lineage ◽  
Cell Fate Decision ◽  
Cell Fate Decisions ◽  
Chemical Signalling ◽  
Fate Decision

AbstractDuring the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.

scholarly journals Variability in β-catenin pulse dynamics in a stochastic cell fate decision in C. elegans

2018 ◽  
Author(s):  
Jason R. Kroll ◽  
Jasonas Tsiaxiras ◽  
Jeroen S. van Zon
Keyword(s):  
Caenorhabditis Elegans ◽  
Cell Fate ◽  
Cell Fusion ◽  
Precursor Cell ◽  
Cell Fate Decision ◽  
Absolute Level ◽  
Cell Fate Decisions ◽  
Pulse Dynamics ◽  
Significant Variability ◽  
Fate Decision

AbstractDuring development, cell fate decisions are often highly stochastic, but with the frequency of the different possible fates tightly controlled. To understand how signaling networks control the cell fate frequency of such random decisions, we studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. Using time-lapse microscopy to measure the single-cell dynamics of two key inhibitors of cell fusion, the Hox gene LIN-39 and Wnt signaling through the β-catenin BAR-1, we uncovered significant variability in the dynamics of LIN-39 and BAR-1 levels. Most strikingly, we observed that BAR-1 accumulated in a single, 1-4 hour pulse at the time of the P3.p cell fate decision, with strong variability both in pulse slope and time of pulse onset. We found that the time of BAR-1 pulse onset was delayed relative to the time of cell fusion in mutants with low cell fusion frequency, linking BAR-1 pulse timing to cell fate outcome. Overall, a model emerged where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced. Our results highlight that timing of cell signaling dynamics, rather than its average level or amplitude, could play an instructive role in determining cell fate.Article summaryWe studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. We uncovered significant variability in the dynamics of LIN-39/Hox and BAR-1/β-catenin levels, two key inhibitors of cell fusion. Surprisingly, we observed that BAR-1 accumulated in a 1-4 hour pulse at the time of the P3.p cell fate decision, with variable pulse slope and time of pulse onset. Our work suggests a model where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced.

Stepwise cell fate decision pathways during osteoclastogenesis at single-cell resolution

2020 ◽  
Vol 2 (12) ◽  
pp. 1382-1390
Author(s):  
Masayuki Tsukasaki ◽  
Nam Cong-Nhat Huynh ◽  
Kazuo Okamoto ◽  
Ryunosuke Muro ◽  
Asuka Terashima ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Cell Fate Decision ◽  
Fate Decision

scholarly journals Decision tree models and cell fate choice

2020 ◽  
Author(s):  
Ivan Croydon Veleslavov ◽  
Michael P.H. Stumpf
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Types ◽  
Lineage Tree ◽  
Tree Models ◽  
Fate Decision ◽  
Average Gene ◽  
Lineage Trees ◽  
Cell Data

AbstractSingle cell transcriptomics has laid bare the heterogeneity of apparently identical cells at the level of gene expression. For many cell-types we now know that there is variability in the abundance of many transcripts, and that average transcript abun-dance or average gene expression can be a unhelpful concept. A range of clustering and other classification methods have been proposed which use the signal in single cell data to classify, that is assign cell types, to cells based on their transcriptomic states. In many cases, however, we would like to have not just a classifier, but also a set of interpretable rules by which this classification occurs. Here we develop and demonstrate the interpretive power of one such approach, which sets out to establish a biologically interpretable classification scheme. In particular we are interested in capturing the chain of regulatory events that drive cell-fate decision making across a lineage tree or lineage sequence. We find that suitably defined decision trees can help to resolve gene regulatory programs involved in shaping lineage trees. Our approach combines predictive power with interpretabilty and can extract logical rules from single cell data.

scholarly journals Newly developed single-cell computational approach elucidates the stabilization of Oct4 expression in the E3.25 mouse preimplantation embryo

2018 ◽  
Author(s):  
Daniela Gerovska ◽  
Marcos J. Arauzo-Bravo
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Clustering Algorithm ◽  
Preimplantation Embryo ◽  
Outer Cell ◽  
Cell Fate Decision ◽  
Oct4 Expression ◽  
Mouse Preimplantation Embryo ◽  
Fate Decision ◽  
Canonical Wnt

AbstractThe time of onset of the second cell fate decision in the mouse preimplantation embryo is still unknown. Ohnishi et al. (2014) looked for cell heterogeneity in the ICM at E3.25 that could indicate the time preceding the apparent segregation of PE and EPI at E3.5, but were not able to detect an early splitting transcriptomics event using state-of-the-art clustering techniques. We developed a new clustering algorithm, hierarchical optimal k-means (HOkM), and identified from single cell (sc) transcriptomics microarray data two groups of ICM cells during the 32 to 64 mouse embryo transition: from embryos with less than 34 cells, and more than 33 cells, corresponding to two developmental sub-stages. The genes defining these sub-stages indicate that the development of the embryo to 34 cells triggers a dramatic event as a result of which Bsg is high expressed, the canonical Wnt pathway is activated, Oct4 is stabilized to high expression and the chromatin remodeling program is initialized to establish a very early narve pluripotent state from the preceding totipotency. We characterized our HOkM partition comparing with independent scRNA-seq datasets. It was staggering to discover that from the 3.4360×1010 possible bi-partitions of the E3.25 data of Ohnishi et al. (2014), our HOkM discovered one partition that shares the biological features of the early and late 32 ICM cells of Posfai et al. (2017). We propose that the stabilization of Oct4 expression is a non-cell autonomous process that requires a minimal number of four inner cell contacts acquired during the transition from a homogeneous outer-cell environment to a heterogeneous inner/outer cell environment formed by the niche of a kernel of at least six inner cells covered by trophectoderm.

scholarly journals A single-cell resolved cell-cell communication model explains lineage commitment in hematopoiesis

Development ◽  
2021 ◽  
Vol 148 (24) ◽  
Author(s):  
Megan K. Rommelfanger ◽  
Adam L. MacLean
Keyword(s):  
Cell Fate ◽  
Cell Communication ◽  
Communication Model ◽  
Cell Fate Decision ◽  
Cell Coupling ◽  
Environmental Signals ◽  
Cell Fate Decisions ◽  
Wide Range ◽  
Fate Decision ◽  
Cell Cell

ABSTRACT Cells do not make fate decisions independently. Arguably, every cell-fate decision occurs in response to environmental signals. In many cases, cell-cell communication alters the dynamics of the internal gene regulatory network of a cell to initiate cell-fate transitions, yet models rarely take this into account. Here, we have developed a multiscale perspective to study the granulocyte-monocyte versus megakaryocyte-erythrocyte fate decisions. This transition is dictated by the GATA1-PU.1 network: a classical example of a bistable cell-fate system. We show that, for a wide range of cell communication topologies, even subtle changes in signaling can have pronounced effects on cell-fate decisions. We go on to show how cell-cell coupling through signaling can spontaneously break the symmetry of a homogenous cell population. Noise, both intrinsic and extrinsic, shapes the decision landscape profoundly, and affects the transcriptional dynamics underlying this important hematopoietic cell-fate decision-making system. This article has an associated ‘The people behind the papers’ interview.

Suppressors of a lin-12 hypomorph define genes that interact with both lin-12 and glp-1 in Caenorhabditis elegans.

Genetics ◽  
1993 ◽  
Vol 135 (3) ◽  
pp. 765-783 ◽  
Author(s):  
M Sundaram ◽  
I Greenwald
Keyword(s):  
Caenorhabditis Elegans ◽  
Cell Fate ◽  
Gene Dosage ◽  
Egg Laying ◽  
Loss Of Function ◽  
Cell Fate Decision ◽  
Cell Fates ◽  
Cell Fate Decisions ◽  
Suppressor Mutations ◽  
Fate Decision

Abstract The lin-12 gene of Caenorhabditis elegans is thought to encode a receptor which mediates cell-cell interactions required to specify certain cell fates. Reversion of the egg-laying defective phenotype caused by a hypomorphic lin-12 allele identified rare extragenic suppressor mutations in five genes, sel-1, sel-9, sel-10, sel-11 and sel(ar40) (sel = suppressor and/or enhancer of lin-12). Mutations in each of these sel genes suppress defects associated with reduced lin-12 activity, and enhance at least one defect associated with elevated lin-12 activity. None of the sel mutations cause any obvious phenotype in a wild-type background. Gene dosage experiments suggest that sel-1 and sel(ar40) mutations are reduction-of-function mutations, while sel-9 and sel-11 mutations are gain-of-function mutations. sel-1, sel-9, sel-11 and sel(ar40) mutations do not suppress amorphic lin-12 alleles, while sel-10 mutations are able to bypass partially the requirement for lin-12 activity in at least one cell fate decision. sel-1, sel-9, sel-10, sel-11 and sel(ar40) mutations are also able to suppress the maternal-effect lethality caused by a partial loss-of-function allele of glp-1, a gene that is both structurally and functionally related to lin-12. These sel genes may therefore function in both lin-12 and glp-1 mediated cell fate decisions.

scholarly journals Defining multistep cell fate decision pathways during pancreatic development at single‐cell resolution

2019 ◽  
Vol 38 (8) ◽  
Author(s):  
Xin‐Xin Yu ◽  
Wei‐Lin Qiu ◽  
Liu Yang ◽  
Yu Zhang ◽  
Mao‐Yang He ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Cell Fate Decision ◽  
Pancreatic Development ◽  
Fate Decision
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